Whisper Small Dv - smallsuper
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1777
- Wer: 64.9793
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1305 | 1.6350 | 500 | 0.1777 | 64.9793 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.8.0+cu129
- Datasets 3.6.0
- Tokenizers 0.22.1
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Model tree for smallsuper/whisper-small-dv
Base model
openai/whisper-smallDataset used to train smallsuper/whisper-small-dv
Evaluation results
- Wer on Common Voice 13test set self-reported64.979